A.B. Rodrigues

Probabilistic Assessment of Available Transfer Capability Based on Monte Carlo Method With Sequential Simulation

The objective of this paper is to assess the chronological variations in the available transfer capability (ATC) caused by uncertainties associated with hourly load fluctuations and equipment unavailabilities. The system states resulting from these uncertainties are generated using the Monte Carlo method with sequential simulation (MCMSS). The ATC for each generated state is evaluated through a linear dc optimal power flow (OPF). The test results, with a modified version of the IEEE Reliability Test System, demonstrate that the time-dependent uncertainties have a significant impact on the ATC. These effects have been assessed through statistical indexes such as expected values, box plot, and percentiles

Distribution network reconfiguration with reliability constraints

Electric distribution networks reconfiguration is carried out by the opening/closing of switching devices while keeping the feeders radial topology. Traditionally, the reconfiguration of distribution networks has been implemented aiming to: minimize electric losses in the conductors, to enhance voltage profiles and balance the feeders loads. However, the proposed methodologies for achieving these objectives do not include the reconfiguration impacts on the system reliability indices. The main aim of this paper is to present a methodology for reconfigurating a distribution network with the objective of minimizing the electric losses taking into account constraints associated with: overloads, voltage drops and violation of the targets for reliability indices. The proposed methodology for solving this problem is based on the parallel simulated annealing algorithm. This methodology allows the generation of candidate solutions without violating topological constraints. The proposed model has been validated and tested in standard distribution systems.

Solution of simultaneous transfer capability problem by means of Monte Carlo simulation and primal-dual interior-point method

This paper has as an objective the evaluation of the maximum simultaneous transfer capability using probabilistic methods to include uncertainties associated with load fluctuations and equipment availability. The scenarios resulting from these uncertainties are generated using Monte-Carlo simulation. The maximum simultaneous transfer capability of each generated state is evaluated using linear optimisation based on primal-dual interior-point method. The sample of system states is used to obtain the probability distribution and expected value of the maximum simultaneous transfer capability. Case studies with IEEE RTS-96 system are presented and discussed.

A new methodology for probabilistic short-circuit evaluation with applications in power quality analysis

The main aim of this paper is to propose a probabilistic short-circuit approach to generate the probability distributions of the System Average RMS Variation Index (SARFI) index. The proposed methodology is based on the combination of the admittance summation method in phase coordinates with the Monte Carlo method. This new approach has been tested in a feeder belonging to an electricity distribution company in the Northeast of Brazil to generate the probability distributions of the SARFI index. The tests results demonstrated that the proposed model is a powerful tool to stochastic prediction of voltage sags.

Modelling of faults on overhead lines in distribution systems using the admittance summation method

Faults analysis in generation/transmission systems is generally done by using the method of symmetrical components. However, this technique is not suitable for faults analysis in distribution networks. This problem is caused by the fact that distribution networks are naturally unbalanced. A very used alternative to overcome this difficulty is the application of the phase coordinates method. This method has basically four versions: Gauss-Zbus method, Kersting method, hybrid compensation method and admittance summation method. In this paper, a model for faults on transmission lines of radial distribution systems is proposed. The proposed model is based upon a combination of the admittance summation method and the Kron reduction method to eliminate the nodes introduced into the electric network due to the connection of fault admittance. The methodology proposed in this paper has been tested in a feeder belonging to a distribution company in Northeast of Brazil.

Probabilistic framework for assessment of bilateral transactions in a competitive environment

This paper has as an objective to assess the feasibility of bilateral transactions using probabilistic methods to include uncertainties associated with peak load forecasting and components outage. The scenarios originated from these uncertainties are generated using Monte-Carlo simulation. The bilateral transactions feasibility is assessed for each generated state using linear optimization based in primal-dual interior-point method. The sample of system states is used to obtain the probability distributions and the expected value associated with a bilateral transaction. Case studies with IEEE Reliability Test System-1996 are presented and discussed.

Probabilistic Assessment of Voltage Sag in radial distribution networks

The main aim of this paper is to develop a stochastic model for carrying out a predictive assessment of voltage sag (PAVS) in radial distribution systems. The PAVS estimates the voltage sag characteristics (magnitude, duration and frequency) and evaluates probabilistic indices of power quality in a distribution system. The proposed model is based on the combination of the Monte Carlo simulation method (MCSM) and the admittance summation method in phase coordinates. The MCSM is used to model uncertainties associated with fault scenarios and the admittance summation method (ASM) is used to evaluate the fault currents. The duration of the voltage sag has been estimated using the currentxtime curves of the protection devices (fuses, breakers and reclosers). The proposed methodology has been tested in a feeder belonging to the Maranhao electricity utility (CEMAR), Brazil, and the results indicate that the proposed methodology is a good tool for studies of sags in distribution systems.

Evaluation of well-being indices for power transactions in deregulated environment

This paper presents an application of system well-being analysis in the assessment of bilateral transactions. This application has the objective of siding system operators to interpret probabilistic indices associated with bilateral transactions. The feasibility of bilateral transactions has been assessed through the definition of system operation states. The probabilities associated with these system operation states have been evaluated using Monte-Carlo Simulation method. Furthermore, expected curtailments and probabilities distributions of the bilateral transactions have been evaluated for several system conditions. Case studies with the New Brunswick Power Company system are presented and discussed.